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    "# 多层感知机\n",
    "`chap_perceptrons`\n",
    "\n",
    "在本章中，我们将第一次介绍真正的*深度*网络。    \n",
    "\n",
    "最简单的深度网络称为*多层感知机*。多层感知机由多层神经元组成，每一层与它的上一层相连，从中接收输入，同时每一层也与它的下一层相连，影响当前层的神经元。  \n",
    "\n",
    "当我们训练容量较大的模型时，我们面临着*过拟合*的风险。\n",
    "因此，本章将从基本的概念介绍开始讲起，包括*过拟合*、*欠拟合*和模型选择。  \n",
    "为了解决这些问题，本章将介绍*权重衰减*和*暂退法*等正则化技术。  \n",
    "我们还将讨论数值稳定性和参数初始化相关的问题，  \n",
    "这些问题是成功训练深度网络的关键。 \n",
    "\n",
    "在本章的最后，我们将把所介绍的内容应用到一个真实的案例：房价预测。  \n",
    "\n",
    "toc\n",
    " - [mlp](01_mlp.ipynb)\n",
    " - [mlp-scratch](02_mlp-scratch.ipynb)\n",
    " - [mlp-concise](03_mlp-concise.ipynb)\n",
    " - [underfit-overfit](04_underfit-overfit.ipynb)\n",
    " - [weight-decay](05_weight-decay.ipynb)\n",
    " - [dropout](06_dropout.ipynb)\n",
    " - [backprop](07_backprop.ipynb)\n",
    " - [numerical-stability-and-init](08_numerical-stability-and-init.ipynb)\n",
    " - [environment](09_environment.ipynb)\n",
    " - [kaggle-house-price](10_kaggle-house-price.ipynb)\n",
    "\n"
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